Percival is an implementation of the augmented Lagrangian solver described in
S. Arreckx, A. Lambe, Martins, J. R. R. A., & Orban, D. (2016).
A Matrix-Free Augmented Lagrangian Algorithm with Application to Large-Scale Structural Design Optimization.
Optimization And Engineering, 17, 359โ384. doi:10.1007/s11081-015-9287-9
with internal solver tron
from JSOSolvers.jl.
To use Percival, you have to pass it an NLPModel.
If you use Percival.jl in your work, please cite using the format given in CITATION.bib.
Use ]
to enter pkg>
mode of Julia, then
pkg> add https://github.com/JuliaSmoothOptimizers/Percival.jl
You can solve an JuMP model m
by using NLPModels to convert it.
using NLPModelsJuMP, Percival
nlp = MathOptNLPModel(m)
output = percival(nlp)